[PDF] Top 20 Short Term Electrical Load Forecasting by Artificial Neural Network
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Short Term Electrical Load Forecasting by Artificial Neural Network
... peak load, to insure that sufficient power can be delivered to the customers whenever they need ...Power Load Forecasting (EPLF) is a vital process in the planning of electricity industry and the ... See full document
4
A SOM-based hierarchical model to short-term load forecasting
... feed-forward neural network trained with the standard error backpropagation algorithm ...to short-term forecasting of daily peak load, total daily energy, and hourly daily ... See full document
6
Hybrid artificial intelligence algorithms for short-term load and price forecasting in competitive electric markets
... followed by emerging consumption patterns (with an overall growth tendency), a more deregulated supply, where the role of producer and consumer can intersect, ...the load profile [11], leading to poorly ... See full document
111
An Integrated Intelligent Neuro-Fuzzy Algorithm for Long-Term Electricity Consumption: Cases of Selected EU Countries
... forecasted electrical consumption by the integration of a neural network, a time series and ANOVA ...integrated artificial neural network and genetic algorithm framework ... See full document
20
Short term load forecasting: two stage modelling
... electricity load demand in the area covered by a utility situated in the Seattle, USA, called Puget Sound Power and Light ...(Artificial Neural Networks) to model short-run dynamics and ... See full document
15
Short-term electricity prices forecasting in a competitive market: A neural network approach
... a neural network approach for forecasting short-term electricity ...price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices ... See full document
8
A Neural Network Model for Forecasting CO2 Emission
... and neural network-type models (Gallo et ...for forecasting, providing excellent results when used for long- term prediction, while not satisfactory when used for short-term ... See full document
6
Electricity Load Forecasting based on Framelet Neural Network Technique
... of neural networks in short-term load ...The neural network was able to determine the nonlinear relationship that exists between the historical load data supplied to it ... See full document
4
Non Intrusive Load Identification with Power and Impedance obtained from Smart Meters
... An artificial neural network was trained with the electrical features obtained for each typical ...each load is indicated as an output of the neural network, allowing ... See full document
10
Artificial Neural Networks versus Box-Jenkins Methodology in Tourism Demand Analysis
... proposed by Box and Jenkins, in 1970, makes it possible to undertake an analysis of the behaviour of time series, based on a joint double study: on the one hand, there is an autoregressive component that is ... See full document
19
A self-adaptive evolutionary fuzzy model for load forecasting problems on smart grid environment
... backpropagation neural network to perform forecasts over a MG environment, however, the accuracy of their results had been com- promised due to large load variations in the small office building that ... See full document
18
Pesqui. Oper. vol.35 número1
... (denoted by WD-ANN) that combines the Artificial Neural Networks (ANN) and the Wavelet Decomposition (WD) to generate short-term global horizontal solar ra- diation forecasting, ... See full document
18
A hierarchical neural model in short-term load forecasting
... named artificial neural net- work short-term load forecaster ...two neural forecasters—one forecasts the base load, and the other predicts the change in ...for ... See full document
8
Short-Term Load Forecasting Using Artificial Neural Network
... Electric load demand is a function of weather variables and human social activities, industrial activities as well as community developmental level to mention a few ...required load forecasts can be ... See full document
6
A hierarchical hybrid neural model in short-term load forecasting
... feed-forward neural network trained with the standard error back- propagation algorithm ...to short-term forecasting of daily peak load, total daily energy, and hourly daily ... See full document
6
Forecasting Short Term Electricity Price Using Artificial Neural Network and Fuzzy Regression
... price forecasting the exact model of the system is built ...methods artificial intelligent methods have been used in this field ...recently. Artificial neural networks (ANNs) have been applied ... See full document
8
Forecasting the Portuguese stock market time series by using artificial neural networks
... that neural networks can be used to uncover the non-linearity that exists in the financial ...approach by analysing some of the deterministic/stochastic characteristics of the Portuguese stock exchange ... See full document
14
Diagnóstico do ceratocone baseado no Orbscan com o auxílio de uma rede neural.
... Java Neural Network 1.1 foi criada uma rede neural artificial para classificar os exames entre os dois grupos (normais e portadores de ...rede neural artificial representa uma ... See full document
4
Tourism demand modeling and forecasting with artificial neural network models: The Mozambique case study
... The neural network model used is of the multilayer type, having used three distinct layers, namely an input layer, with the previous twelve months plus the selected variables in its entrance; a hidden layer ... See full document
18
A Neural Network Approach to Time Series Forecasting
... A univariate time series is a sequence of observations of the same random variable at different times, normally at uniform intervals. The goal of univariate time series data mining is to predict future values of a given ... See full document
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